GPT-5.5 vs o3-pro
GPT-5.5 (2026) and o3-pro (2025) are frontier-tier reasoning models from OpenAI. GPT-5.5 ships a 1M-token context window, while o3-pro ships a not-yet-sourced context window. On Google-Proof Q&A, GPT-5.5 leads by 9.6 pts. On pricing, GPT-5.5 costs $5/1M input tokens versus $20/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
GPT-5.5 is ~300% cheaper at $5/1M; pay for o3-pro only for coding workflow support.
Specs
Pricing and availability
| GPT-5.5 | o3-pro | |
|---|---|---|
| Input price | $5/1M tokens | $20/1M tokens |
| Output price | $30/1M tokens | $80/1M tokens |
| Providers |
Capabilities
| GPT-5.5 | o3-pro | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | GPT-5.5 | o3-pro |
|---|---|---|
| Google-Proof Q&A | 93.6 | 84.0 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has GPT-5.5 at 93.6 and o3-pro at 84, with GPT-5.5 ahead by 9.6 points. The largest visible gap is 9.6 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint is close: both models cover vision, multimodal input, reasoning mode, function calling, and tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, GPT-5.5 lists $5/1M input and $30/1M output tokens, while o3-pro lists $20/1M input and $80/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-5.5 lower by about $25.50 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose GPT-5.5 when coding workflow support and lower input-token cost are central to the workload. Choose o3-pro when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which is cheaper, GPT-5.5 or o3-pro?
GPT-5.5 is cheaper on tracked token pricing. GPT-5.5 costs $5/1M input and $30/1M output tokens. o3-pro costs $20/1M input and $80/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 or o3-pro open source?
GPT-5.5 is listed under Proprietary. o3-pro is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.5 or o3-pro?
Both GPT-5.5 and o3-pro expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.5 or o3-pro?
Both GPT-5.5 and o3-pro expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, GPT-5.5 or o3-pro?
Both GPT-5.5 and o3-pro expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run GPT-5.5 and o3-pro?
GPT-5.5 is available on OpenAI API. o3-pro is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.